Good morning Sebastiano,
I found your problem interesting and I thought I would
respond in this fashion. I have done quite a bit of research
on similar layered databases on fluvial mineral deposits and
found that if one did vertical (at right angles to the
contacts of the layers) variograms on the raw data and
obtained a variogram with no drift. then one could be sure
that all these layers you have split your data have similar
spatial characteristics. It would then not be necessary to
examine the horizontal spatial characteristics of each
individual layer, but rather have one standardized variogram
for all of them. If the reverse is true ie drift in the
vertical variogram, then one must look critically at the
data for some phenominum on which one can subdivide. For
instance in fluvial (river) deposits different material
types, drastically different particle size etc according to
what you are studying. I found generally that the lag
distance at which the drift commenced was the width of the
thinnest horizon in the case of two different populations,
but it does not tell you whether it is the top or bottom
layer. This must then be done by scrutinization of your data
in the vetical plane. Once your data is split you can then
do variography on each one of the two layers in the
horizontal plane modelling the anistropy of the variance
separately, This should only be done once you have again
checked these two layers with vertical variograms for drift.
If there are more than two populations present then the
process can be repeated until all your layers have vertical
variograms with no drift and therefore you have split your
data correctly.
Hope this helps
Regards
Bill Northrop
-----Original Message-----
From: [EMAIL PROTECTED] [
mailto:[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]> Behalf Of
sebastiano trevisani
Sent: Monday, August 28, 2006 9:57 AM
To: Isobel Clark
Cc: [email protected]
Subject: Re: AI-GEOSTATS: Re: standardized anomaly
Hi Isobel
I would like to use this transformation to deal with a
3D data set characterized by a peculiarity (well, this
is quite common!) in the horizontal spatial variability.
In particular if I divide the dataset in horizontal
layers I see that horizontal variograms show a similar
shape but with a re-scaled variance.
So, my idea, in order to speed up the process of
interpolation, consists to calculate the standardized
anomaly for each layer and use the same calculated
variogram (well, now it is a kind of standardized
variogram calculated using all layers)) during
interpolation with a 3D routine. Yes, in reality this is
only a trick ...because I`m simply performing a series
of 2D interpolations along layers. This because of, once
the data have been transformed, it is not reasonable to
use during interpolation samples coming from different
horizontal layers.........
Sincerely
Sebastiano
At 14.06 25/08/2006, Isobel Clark wrote:
Sebastiano
You will be fine so long as you actually have a
"stationary" phenomenon. That is, there is a
constant mean and standard deviation over your
study area -- no trends, no discontinuities, no
changes of behaviour. Such a transformation also
assumes that your data follow a fairly symmetrical
histogram.
Your semi-variogram will look exaclty the same as
your 'raw' data semi-variogram but should have a
sill around 1.
Isobel
http://www.kriging.com <http://www.kriging.com/>
Sebastiano Trevisani
<[EMAIL PROTECTED]> wrote:
Dear list member
A procedural question for you.......
I'm thinking to transform my data in a
standardized anomaly [i.e.
(raw datum- sample average)/sample standard
deviation)] and then I`ll
perfom the geostatistical analysis on these
transformed data. At
first glance, I don't see problem in the
back-transformation of
interpolated data and in the correct evaluation
of estimation
variance. Am I wrong?
Sincerely
Sebastiano
+
+ To post a message to the list, send it to
[email protected]
+ To unsubscribe, send email to majordomo@
jrc.it with no subject and "unsubscribe
ai-geostats" in the message body. DO NOT SEND
Subscribe/Unsubscribe requests to the list
+ As a general service to list users, please
remember to post a summary of any useful
responses to your questions.
+ Support to the forum can be found at
http://www.ai-geostats.org/
